Country intelligence page
Bangladesh BGD
Operation Mobility Monitoring due to Disasters at Admin 1. Every comparison below is confined to this operation, because operations differ in geographic scope, cadence and method and are not additive.
Comparability flags on this comparison
- No comparable previous round
What changed?MOSAIC-derived
No previous round is available in this operation, so no comparison can be made. Every area below is reported without a baseline.
Areas without a usable baseline
| Area | Latest | Baseline | Change | Momentum | Comparability | Analysis |
|---|---|---|---|---|---|---|
| Chittagong | 1,212,461 | Not reported | n/a | Not reported |
| |
| Dhaka | 795,798 | Not reported | n/a | Not reported |
| |
| Rajshahi | 659,000 | Not reported | n/a | Not reported |
| |
| Barisal | 594,628 | Not reported | n/a | Not reported |
| |
| Rangpur | 565,128 | Not reported | n/a | Not reported |
| |
| Sylhet | 436,127 | Not reported | n/a | Not reported |
| |
| Khulna | 418,146 | Not reported | n/a | Not reported |
| |
| Mymensingh | 274,239 | Not reported | n/a | Not reported |
|
Methodology and provenance
- Source
- International Organization for Migration (IOM), Displacement Tracking Matrix (DTM). Public API v3.
- Endpoint
- /v3/displacement/admin1
- Geographic level
- Admin 1
- Operation
- Mobility Monitoring due to Disasters
- Reporting period
- Not stated to 31 Oct 2025
- Assessment round
- Round 1 compared with round none
- Retrieved
- 2026-09-04T01:33:49.683Z
- Calculation
- Rows are summed to a present-IDP figure per area and round, then the latest round is compared with the preceding round of the same operation. Areas present in only one of the two rounds are reported as such and are never treated as zero.
Known limitations
- An area that disappears between rounds may have ceased to be assessed rather than ceased to host displacement.
- A newly reported area may be newly affected or newly assessed. The API does not distinguish between these.
- Threshold bands are MOSAIC monitoring settings and are not calibrated to this country's assessment cadence.
MOSAIC-derived indicator. Not an IOM classification.
National displacement timeline
Present IDPs by assessment round within the Mobility Monitoring due to Disasters operation. Breaks in the line mark non-consecutive round numbers, where an intervening round exists that this series does not include.
Methodology and provenance
- Source
- International Organization for Migration (IOM), Displacement Tracking Matrix (DTM). Public API v3.
- Endpoint
- /v3/displacement/admin1
- Geographic level
- Admin 1
- Operation
- Mobility Monitoring due to Disasters
- Reporting period
- 2025-10-31
- Assessment round
- Round 1
- Retrieved
- 2026-09-04 01:33 UTC
- Calculation
- Present IDP figures are summed across all disaggregated source rows for each area, then across areas, for every round of the selected operation.
Known limitations
- Figures may be estimates derived from key informants and secondary sources rather than exact enumeration.
- Assessment coverage and cadence vary by country and operation, so cross-country comparison of change rates is not supported.
- A change in a recorded figure may reflect population movement, altered assessment coverage, changed access, or enumeration method, and the API does not distinguish between these.
- The public API exposes aggregated non-sensitive figures only, and does not carry the full detail of the underlying DTM datasets.
Admin 1 ranking, latest round
Areas ranked by present IDPs reported in the latest round. Bar length is proportional to the largest area.
- Not reportedChittagong1,212,461
- Not reportedDhaka795,798
- Not reportedRajshahi659,000
- Not reportedBarisal594,628
- Not reportedRangpur565,128
- Not reportedSylhet436,127
- Not reportedKhulna418,146
- Not reportedMymensingh274,239
Methodology and provenance
- Source
- International Organization for Migration (IOM), Displacement Tracking Matrix (DTM). Public API v3.
- Endpoint
- /v3/displacement/admin1
- Geographic level
- Admin 1
- Operation
- Mobility Monitoring due to Disasters
- Reporting period
- 31 Oct 2025
- Assessment round
- Round 1
- Retrieved
- 2026-09-04 01:33 UTC
- Calculation
- Areas assessed in the latest round of this operation, ranked by summed present IDP individuals. Momentum shown alongside is the change from the preceding round.
Known limitations
- Only areas assessed in the latest round appear. An unassessed area is absent, not zero.
- Bar length encodes the reported figure only. It carries no information about area size, population or need.
MOSAIC-derived indicator. Not an IOM classification.
Anomaly signalsMOSAIC-derived
Areas whose latest figure moved unusually relative to their own recent history in this operation. Each signal names the rule that fired and the evidence behind it. A signal is a cue for collection, not a finding.
- ChittagongNewly observed location
- Latest
- 1,212,461
- Baseline
- Not reported
- Magnitude
- 1212461.00
- Basis
- 1 obs, low
The unit reports displacement in the latest round and has no prior observation in this operation. Fewer than three observations in this operation. The historical baseline is too short to characterise normal variation.
- DhakaNewly observed location
- Latest
- 795,798
- Baseline
- Not reported
- Magnitude
- 795798.00
- Basis
- 1 obs, low
The unit reports displacement in the latest round and has no prior observation in this operation. Fewer than three observations in this operation. The historical baseline is too short to characterise normal variation.
- RajshahiNewly observed location
- Latest
- 659,000
- Baseline
- Not reported
- Magnitude
- 659000.00
- Basis
- 1 obs, low
The unit reports displacement in the latest round and has no prior observation in this operation. Fewer than three observations in this operation. The historical baseline is too short to characterise normal variation.
- BarisalNewly observed location
- Latest
- 594,628
- Baseline
- Not reported
- Magnitude
- 594628.00
- Basis
- 1 obs, low
The unit reports displacement in the latest round and has no prior observation in this operation. Fewer than three observations in this operation. The historical baseline is too short to characterise normal variation.
- RangpurNewly observed location
- Latest
- 565,128
- Baseline
- Not reported
- Magnitude
- 565128.00
- Basis
- 1 obs, low
The unit reports displacement in the latest round and has no prior observation in this operation. Fewer than three observations in this operation. The historical baseline is too short to characterise normal variation.
- SylhetNewly observed location
- Latest
- 436,127
- Baseline
- Not reported
- Magnitude
- 436127.00
- Basis
- 1 obs, low
The unit reports displacement in the latest round and has no prior observation in this operation. Fewer than three observations in this operation. The historical baseline is too short to characterise normal variation.
- KhulnaNewly observed location
- Latest
- 418,146
- Baseline
- Not reported
- Magnitude
- 418146.00
- Basis
- 1 obs, low
The unit reports displacement in the latest round and has no prior observation in this operation. Fewer than three observations in this operation. The historical baseline is too short to characterise normal variation.
- MymensinghNewly observed location
- Latest
- 274,239
- Baseline
- Not reported
- Magnitude
- 274239.00
- Basis
- 1 obs, low
The unit reports displacement in the latest round and has no prior observation in this operation. Fewer than three observations in this operation. The historical baseline is too short to characterise normal variation.
Methodology and provenance
- Source
- International Organization for Migration (IOM), Displacement Tracking Matrix (DTM). Public API v3.
- Endpoint
- /v3/displacement/admin1
- Geographic level
- Admin 1
- Operation
- Mobility Monitoring due to Disasters
- Reporting period
- 2025-10-31
- Assessment round
- Round 1
- Retrieved
- 2026-09-04 01:33 UTC
- Calculation
- Transparent statistical rules applied to each area's own trailing series within the operation. No model is fitted and no learned parameters are used.
Known limitations
- An anomaly can be produced by a change in assessment coverage or method rather than by population movement.
- Areas with short histories are flagged as low quality because normal variation cannot be characterised.
- The public API supplies no adjacency graph, so no claim of spatial contiguity is made.
MOSAIC-derived indicator. Not an IOM classification.
Geographic concentrationMOSAIC-derived
Displacement is comparatively dispersed across 8 assessed units, with 53.8 per cent in the largest 3.
| Area | Present IDPs | Share |
|---|---|---|
| Chittagong | 1,212,461 | 24.5% |
| Dhaka | 795,798 | 16.1% |
| Rajshahi | 659,000 | 13.3% |
Normalised concentration index: 0.027 on a zero-to-one scale across 8 assessed areas.
Methodology and provenance
- Source
- International Organization for Migration (IOM), Displacement Tracking Matrix (DTM). Public API v3.
- Endpoint
- /v3/displacement/admin1
- Geographic level
- Admin 1
- Operation
- Mobility Monitoring due to Disasters
- Reporting period
- 31 Oct 2025
- Assessment round
- Round 1
- Retrieved
- 2026-09-04 01:33 UTC
- Calculation
- Concentration is computed over the administrative units reported in the selected round of the selected DTM operation. It uses the Herfindahl-Hirschman Index of unit shares, normalised so that zero is an even distribution across assessed units and one is total concentration in a single unit. Units not assessed in the round are absent from the calculation, so a narrowing of assessment coverage will raise measured concentration without any population movement.
Known limitations
- Concentration rises mechanically when assessment coverage narrows, with no population movement required.
MOSAIC-derived indicator. Not an IOM classification.
Coverage and confidenceMOSAIC-derived
What the observation process supports, stated separately from what the figures say.
- Assessed areas, latest
- 8
- Assessed areas, baseline
- n/a
- Rounds in operation
- 1
- Median round interval
- n/a
- Only one round is available, so no round-to-round comparison is possible.
Confidence derivation
The change should not be treated as a monitoring signal on its own. Comparability, coverage or recency conditions materially limit interpretation.
- −45: No comparable previous round in this operation
- −12: Latest assessment is between six months and a year old
- −20: Fewer than three observations of this unit in the operation
- −10: Operation has fewer than three rounds of history
Methodology and provenance
- Source
- International Organization for Migration (IOM), Displacement Tracking Matrix (DTM). Public API v3.
- Endpoint
- /v3/displacement/admin1
- Geographic level
- Admin 1
- Operation
- Mobility Monitoring due to Disasters
- Reporting period
- 2025-10-31
- Assessment round
- Round 1
- Retrieved
- 2026-09-04 01:33 UTC
- Calculation
- MOSAIC confidence describes how well a change is grounded in comparable DTM observations. It begins at 100 and applies fixed deductions for missing baselines, non-consecutive rounds, coverage changes, short unit histories and assessment age. It is a statement about data comparability and recency only. It carries no claim about the cause of a change.
Known limitations
- Confidence describes data comparability and recency only. It carries no claim about the cause of a change.
MOSAIC-derived indicator. Not an IOM classification.
Recorded displacement reason, latest round
Taken directly from the DTM records. This is a source field, not a MOSAIC classification.
| Reason | Present IDPs | Share |
|---|---|---|
| Natural disaster | 4,955,527 | 100.0% |
Methodology and provenance
- Source
- International Organization for Migration (IOM), Displacement Tracking Matrix (DTM). Public API v3.
- Endpoint
- /v3/displacement/admin1
- Geographic level
- Admin 1
- Operation
- Mobility Monitoring due to Disasters
- Reporting period
- 31 Oct 2025
- Assessment round
- Round 1
- Retrieved
- 2026-09-04 01:33 UTC
- Calculation
- The displacementReason field on each source row, summed over the latest round of the selected operation.
Known limitations
- Reason is recorded at assessment. It reflects the reason as reported, and may not capture compound or sequential causes.
Generate analyst brief
A deterministic, template-generated brief covering situation snapshot, key changes, trend, concentration, anomalies, analytic questions, information gaps, collection priorities and methodological caveats. No generative model is in the path, so the same data always produces the same brief.